Executing multiple instructions multiple date (‘MIMD’) programs on a single instruction multiple data (‘SIMD’) machine

ABSTRACT

Executing MIMD programs on a SIMD machine, including establishing on the SIMD machine a plurality of SIMD partitions; booting a first SIMD partition in MIMD mode; executing, on a compute node of the first SIMD partition booted in MIMD mode, a MIMD accelerator program; executing a SIMD program in a second SIMD partition, one instance of the SIMD program executing on each compute node of the second SIMD partition, each instance of the SIMD program carrying out a portion of the data processing effected by the SIMD program; and accelerating, by an instance of the SIMD program through the MIMD accelerator program, a portion of the data processing of the instance of the SIMD program.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The field of the invention is data processing, or, more specifically,methods, apparatus, and products for executing Multiple InstructionsMultiple Data (‘MIMD’) programs on a Single Instruction Multiple Data(‘SIMD’) machine.

2. Description of Related Art

The development of the EDVAC computer system of 1948 is often cited asthe beginning of the computer era. Since that time, computer systemshave evolved into extremely complicated devices. Today's computers aremuch more sophisticated than early systems such as the EDVAC. Computersystems typically include a combination of hardware and softwarecomponents, application programs, operating systems, processors, buses,memory, input/output devices, and so on. As advances in semiconductorprocessing and computer architecture push the performance of thecomputer higher and higher, more sophisticated computer software hasevolved to take advantage of the higher performance of the hardware,resulting in computer systems today that are much more powerful thanjust a few years ago.

Parallel computing is an area of computer technology that hasexperienced advances. Parallel computing is the simultaneous executionof the same task (split up and specially adapted) on multiple processorsin order to obtain results faster. Parallel computing is based on thefact that the process of solving a problem usually can be divided intosmaller tasks, which may be carried out simultaneously with somecoordination. Parallel computing may be implemented in architecturesoptimized to execute in a mode of ‘Single Instruction, Multiple Data’(‘SIMD’) or in a mode of ‘Multiple Instruction, Multiple Data’ (‘MIMD’).This exact terminology, SIMD and MIMD, is from the well-known Flynn'staxonomy, a classification of computer architectures first described byMichael J. Flynn in 1966.

A MIMD machine is a computer in which multiple autonomous processorssimultaneously execute different instructions on different data.Distributed systems are generally recognized to be MIMDarchitectures—either exploiting a single shared memory space or adistributed memory space. Many common computer applications areimplemented with MIMD architectures, including, for example, mostaccounting programs, word processors, spreadsheets, database managers,browsers, web applications, other data communications programs, and soon.

A SIMD machine is a computer that exploits multiple data streams againsta single instruction stream to perform operations which may be naturallyparallelized. SIMD machines are ubiquitous on a small scale, in digitalspeech processors, graphics processors, and the like. In addition,however, SIMD machines also make up the largest, most powerful computersin the world. The BlueGene/L computer architecture, for example, isimplemented with a SIMD architecture. BlueGene/L installations representnine of the twenty-five most powerful computer installations in theworld—according to a current listing of the top 500 supercomputer sitespublished by the TOP500 Project. In fact, most, if not all, of the mostpowerful computers in the world today are SIMD machines.

SIMD machines execute parallel algorithms, typically includingcollective operations. A parallel algorithm can be split up to beexecuted a piece at a time on many different processing devices, andthen put back together again at the end to get a data processing result.Some algorithms are easy to divide up into pieces. Splitting up the jobof checking all of the numbers from one to a hundred thousand to seewhich are primes could be done, for example, by assigning a subset ofthe numbers to each available processor, and then putting the list ofpositive results back together. In this specification, the multipleprocessing devices that execute the individual pieces of a parallelprogram are referred to as ‘compute nodes.’ A SIMD machine is composedof compute nodes and other processing nodes as well, including, forexample, input/output (‘i/o’) nodes, and service nodes.

Parallel algorithms are designed also to optimize the datacommunications requirements among the nodes of a SIMD machine. There aretwo ways parallel processors communicate, shared memory or messagepassing. Shared memory processing needs additional locking technologyfor the data and imposes the overhead of additional processor and buscycles and also serializes some portion of the algorithm. Messagepassing processing uses high-speed data communications networks andmessage buffers, but this communication adds transfer overhead on thedata communications networks as well as additional memory need formessage buffers and latency in the data communications among nodes.Designs of SIMD machines use specially designed data communicationslinks so that the communication overhead will be small but it is theparallel algorithm that decides the volume of the traffic.

The large aggregation of data processing power represented by massivelyparallel SIMD machines is extremely attractive to MIMD applications. TheBlueGene/L architecture produces many teraflops per rack, has a largememory footprint, and low power consumption—all features which wouldmake it very useful if MIMD programs could be run on it. MIMDoperations, however, require a model that allows for independentprograms on each compute. Today the hardware and software for such SIMDmachines are designed only to support applications based on cooperatingnodes, purely parallel SIMD applications. Specialized memory sharing anddata communications technology in SIMD machines, which make the SIMDmachines so powerful, render such SIMD machines useless for MIMDapplications. In the BlueGene example, a processing error on one node ofa partition immediately terminates all data processing operations onevery compute node in the partition—a necessary requirement when all thecompute nodes are running the same SIMD application—but a disaster forMIMD operations.

SUMMARY OF THE INVENTION

Methods, apparatus, and computer program products are disclosed forexecuting MIMD programs on a SIMD machine, the SIMD machine including aplurality of compute nodes, each compute node capable of executing onlya single thread of execution, the compute nodes initially configuredexclusively for SIMD operations, the SIMD machine also including a datacommunications network, the network further including synchronous datacommunications links among the compute nodes, including establishing onthe SIMD machine a plurality of SIMD partitions, each SIMD partitioncomprising a plurality of the compute nodes, the compute nodes in eachSIMD partition electronically isolated from compute nodes in otherpartitions of the SIMD machine and coupled to one another through linksof the network for synchronous data communications for parallel SIMDoperations among the compute nodes in each SIMD partition; booting afirst SIMD partition in MIMD mode; executing, on a compute node of thefirst SIMD partition booted in MIMD mode, a MIMD accelerator program;executing a SIMD program in a second SIMD partition, one instance of theSIMD program executing on each compute node of the second SIMDpartition, each instance of the SIMD program carrying out a portion ofthe data processing effected by the SIMD program; and accelerating, byan instance of the SIMD program through the MIMD accelerator program, aportion of the data processing of the instance of the SIMD program.

The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescriptions of exemplary embodiments of the invention as illustrated inthe accompanying drawings wherein like reference numbers generallyrepresent like parts of exemplary embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary system for executing MIMD programs on aSIMD machine according to embodiments of the present invention.

FIG. 2 sets forth a block diagram of an exemplary compute node useful inexecuting MIMD programs on a SIMD machine according to embodiments ofthe present invention.

FIG. 3A illustrates an exemplary Point To Point Adapter useful insystems that execute MIMD programs on a SIMD machine according toembodiments of the present invention.

FIG. 3B illustrates an exemplary Collective Operations Adapter useful insystems that execute MIMD programs on a SIMD machine according toembodiments of the present invention.

FIG. 4 illustrates an exemplary data communications network optimizedfor point to point operations, useful in systems that executing MIMDprograms on a SIMD machine.

FIG. 5 illustrates an exemplary data communications network optimizedfor collective operations, useful in systems that executing MIMDprograms on a SIMD machine.

FIG. 6 sets forth a functional block diagram illustrating a furtherexemplary system for executing MIMD programs on a SIMD machine accordingto embodiments of the present invention.

FIG. 7 sets forth a flow chart illustrating an exemplary method ofexecuting MIMD programs on a SIMD machine according to embodiments ofthe present invention.

FIG. 8 sets forth a flow chart illustrating an exemplary method ofbooting a SIMD partition in MIMD mode according to embodiments of thepresent invention.

FIG. 9 sets forth a flow chart illustrating a further exemplary methodof executing MIMD programs on a SIMD machine according to embodiments ofthe present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Exemplary methods, apparatus, and computer program products forexecuting Multiple Instructions Multiple Data (‘MIMD’) programs on aSingle Instruction Multiple Data (‘SIMD’) machine according toembodiments of the present invention are described with reference to theaccompanying drawings, beginning with FIG. 1. FIG. 1 illustrates anexemplary system for executing MIMD programs on a SIMD machine accordingto embodiments of the present invention. The system of FIG. 1 includes aSIMD machine (100), a computer configured initially for exclusivelyparallel, collective operations. The system of FIG. 1 also includesnon-volatile memory for the SIMD machine in the form of data storagedevice (118), an output device for the SIMD machine in the form ofprinter (120), and an input/output (‘i/o’) device for the SIMD machinein the form of computer terminal (122). The SIMD machine (100) in theexample of FIG. 1 includes a plurality of compute nodes (102), each ofwhich is capable of executing only a singe thread of execution.

The compute nodes (102) are coupled for data communications by severalindependent data communications networks including:

-   -   a high speed Ethernet network (174) that connects peripherals        through i/o node to compute nodes,    -   a Joint Test Action Group (‘JTAG’) network (104) for out of band        signaling between service nodes, i/o nodes, and compute nodes,    -   a synchronous collective network (106) in which each compute        node connects in a tree structure to three neighboring compute        nodes, with the collective network optimized for massively        parallel collective operations among compute nodes,    -   a synchronous point-to-point network (108), optimized for point        to point operations among compute nodes, in which each compute        node connects in a torus to six neighboring compute nodes        through which each node in the torus can communicate directly or        indirectly with every other compute node in the torus, and    -   a barrier network (109) connecting all compute nodes in an        independent network in which each compute node can signal to all        other compute nodes processing arrival at a parallel processing        barrier, halting further processing until all nodes have        reported arrival at the barrier.

Each data communications network is implemented with data communicationslinks among the compute nodes (102). The data communications linksprovide data communications for parallel operations among the computenodes of the SIMD machine. Point-to-point network (108) is a synchronousdata communications network that includes synchronous datacommunications links connected among the compute nodes so as to organizethe compute nodes in a mesh or torus. Collective network (106) is asynchronous data communications network that includes synchronous datacommunications links connected among the compute nodes so as to organizethe compute nodes in a tree structure.

The compute nodes (102) may be organized in SIMD partitions (130 132). ASIMD partition is an operational group of compute nodes for collectiveparallel operations on a SIMD machine (100). A SIMD partition is a setof compute nodes upon which parallel collective operations of a SIMDapplication execute. Such a SIMD partition may include all the computenodes in a SIMD machine (100) or a subset all the compute nodes. Thecompute nodes in a SIMD partition are electronically isolated fromcompute nodes in other partitions of the SIMD machine. The compute nodesin a SIMD partition are coupled to one another through links of at leastone network for synchronous data communications for parallel SIMDoperations among the compute nodes in the SIMD partition. In the exampleof FIG. 1, several networks connect the compute nodes.

Collective operations are implemented with data communications among thecompute nodes of a SIMD partition. Collective operations are thosefunctions that involve all the compute nodes of an operational group inparallel operations. A collective operation is an operation, amessage-passing computer program instruction that is executedsynchronously, that is, at approximately the same time, by all thecompute nodes in a SIMD partition. Such synchronous operations aresupported by synchronous data communications networks and parallelprocessing barriers. Parallel collective operations can be implementedwith point to point operations. A collective operation requires that allprocesses on all compute nodes within a SIMD partition call the samecollective operation with matching arguments. A ‘broadcast’ is anexample of a collective operations for moving data among compute nodesof a SIMD partition. A ‘reduce’ operation is an example of a collectiveoperation that executes arithmetic or logical functions on datadistributed among the compute nodes of a SIMD partition. A SIMDpartition may be implemented as, for example, an MPI ‘communicator.’

‘MPI’ refers to ‘Message Passing Interface,’ a parallel communicationslibrary, a module of computer program instructions for datacommunications on parallel computers. Examples of parallelcommunications libraries that may be useful or may be improved to beuseful for executing MIMD programs on a SIMD machine according toembodiments of the present invention include MPI and the ‘ParallelVirtual Machine’ (‘PVM’) library. PVM was developed by the University ofTennessee, The Oak Ridge National Laboratory and Emory University. MPIis promulgated by the MPI Forum, an open group with representatives frommany organizations that define and maintain the MPI standard. MPI at thetime of this writing is a de facto standard for communication amongcompute nodes running a parallel program on a distributed memoryparallel computer. This specification sometimes uses MPI terminology forease of explanation, although the use of MPI as such is not arequirement or limitation of the present invention.

Most collective operations are variations or combinations of four basicoperations: broadcast, gather, scatter, and reduce. In a broadcastoperation, all processes specify the same root process, whose buffercontents will be sent. Processes other than the root specify receivebuffers. After the operation, all buffers contain the message from theroot process.

A scatter operation, like the broadcast operation, is also a one-to-manycollective operation. All processes specify the same receive count. Thesend arguments are only significant to the root process, whose bufferactually contains sendcount*N elements of a given datatype, where N isthe number of processes in the given SIMD partition. The send bufferwill be divided equally and dispersed to all processes (includingitself). Each compute node in the SIMD partition is assigned asequential identifier termed a ‘rank.’ After the operation, the root hassent sendcount data elements to each process in increasing rank order.Rank 0 receives the first sendcount data elements from the send buffer.Rank 1 receives the second sendcount data elements from the send buffer,and so on.

A gather operation is a many-to-one collective operation that is acomplete reverse of the description of the scatter operation. That is, agather is a many-to-one collective operation in which elements of adatatype are gathered from the ranked compute nodes into a receivebuffer in a root node.

A reduce operation is also a many-to-one collective operation thatincludes an arithmetic or logical function performed on two dataelements. All processes specify the same ‘count’ and the same arithmeticor logical function. After the reduction, all processes have sent countdata elements from computer node send buffers to the root process. In areduction operation, data elements from corresponding send bufferlocations are combined pair-wise by arithmetic or logical operations toyield a single corresponding element in the root process's receivebuffer. Application specific reduction operations can be defined atruntime. Parallel communications libraries may support predefinedoperations. MPI, for example, provides the following pre-definedreduction operations:

MPI_MAX maximum MPI_MIN minimum MPI_SUM sum MPI_PROD product MPI_LANDlogical and MPI_BAND bitwise and MPI_LOR logical or MPI_BOR bitwise orMPI_LXOR logical exclusive or MPI_BXOR bitwise exclusive or

In addition to compute nodes, the SIMD machine (100) in this exampleincludes input/output (‘I/O’) nodes (110, 114) coupled to compute nodes(102) through one of the data communications networks (174). The I/Onodes (110, 114) provide I/O services between compute nodes (102) andI/O devices (118, 120, 122). I/O nodes (110, 114) are connected for datacommunications 1/0 devices (118, 120, 122) through local area network(‘LAN’) (130).

The SIMD machine (100) also includes a service node (116) coupled to thecompute nodes through one of the networks (104). Service node (116)provides services common to pluralities of compute nodes, loadingprograms into the compute nodes, starting program execution on thecompute nodes, retrieving results of program operations on the computernodes, and so on. Service node (116) runs service applications (143) andcommunicates with users (128) through a service application interface(126) that runs on computer terminal (122). Service applications (143)that execute on the service node (116) include:

-   -   a control application (124), which is a module of computer        program instructions that boots partitions, loads launcher        programs onto compute nodes in SIMD partitions booted in MIMD        mode, and administers error conditions detected on compute        nodes,    -   a scheduler (140), which is a module of computer program        instructions that schedules data processing jobs on the SIMD        machine, including installing SIMD programs on compute nodes and        passing MIMD jobs along to a MIMD dispatcher for installation on        SIMD partitions booted in MIMD mode; and    -   a MIMD dispatcher (139), which is a module of computer program        instructions that installs MIMD programs on compute nodes in        SIMD partitions booted in MIMD mode.

In the example of FIG. 1, all the compute nodes (102) are initiallyconfigured exclusively for SIMD operations, and the system of FIG. 1operates generally to execute MIMD programs (158) on a SIMD machine(100) according to embodiments of the present invention by establishingon the SIMD machine a plurality of SIMD partitions (130, 132); booting afirst SIMD partition (130) in MIMD mode; executing, on a compute node(102) of the first SIMD partition (130) booted in MIMD mode, a MIMDaccelerator program (161); executing a SIMD program (151) in a secondSIMD partition (132), one instance (153, 155, 157, 159) of the SIMDprogram (151) executing on each compute node (102) of the second SIMDpartition (132), each instance of the SIMD program carrying out aportion of the data processing effected by the SIMD program; andaccelerating, by an instance of the SIMD program through the MIMDaccelerator program, a portion of the data processing of the instance ofthe SIMD program.

Booting a SIMD partition (130) in MIMD mode provides the capability ofexecuting, not only a MIMD accelerator program, but also executing bylauncher programs (135) multiple additional MIMD programs (158) as wellon any or all of the compute nodes in a SIMD partition booted in MIMDmode. MIMD accelerator programs in fact represent an additional categoryof MIMD programs. Each MIMD program (158) is a module of computerprogram instructions that autonomously executes different instructionson different data. That is, each MIMD program has computer programinstructions that typically are not the same instructions executed byother MIMD programs, and each MIMD program operates on data thattypically is not the same data processed by other MIMD programs. Bootinga SIMD partitions (130) in MIMD mode may be carried out by setting, inoperating systems on the compute nodes of a SIMD partition, flagsindicating MIMD operation; loading onto the compute nodes of the SIMDpartition a launcher program (135); initializing with link trainingsynchronous data communications among links of the network among computenodes in the SIMD partition; initializing, with a parallel processingbarrier, parallel operations among the compute nodes of the SIMDpartition; and executing a launcher program (135) on each compute nodein the SIMD partition.

A MIMD accelerator program is a MIMD program is a MIMD program that iscapable of performing some portion of the data processing of a SIMDprogram faster than the SIMD program could do it without the acceleratorprogram. An ‘accelerator’ generally is some combination of computerhardware and software that performs some function faster than ispossible in software running on a normal, general purpose processor.Examples of prior art accelerators include floating point units(‘FPUs’), digital signal processors (‘DSPs’), and graphics processingunits (‘GPUs’). Prior art accelerators, DSPs and GPUs, for example,typically were SIMD accelerators that received requests for accelerationfrom general purpose CPUs which frequently in prior art were MIMDdevices. That is, the typical pattern in prior art was that MIMDprograms requested acceleration from SIMD programs. In systems thatexecute MIMD programs on a SIMD machine according to embodiments of thepresent invention, however, it is a SIMD program that uses a MIMDprogram for acceleration.

In systems that execute MIMD programs on a SIMD machine according toembodiments of the present invention there is no one-to-one relationshipbetween SIMD nodes and accelerators. Such a one-to-one relationship wascommon in the prior art: a general purpose CPU typically would have asingle FPU, a single GPU, or a single DSP. In systems that execute MIMDprograms on a SIMD machine according to embodiments of the presentinvention, however, one instance of a SIMD program may use multipleaccelerator programs executing simultaneously on multiple compute nodesof a SIMD partition booted in MIMD mode. In addition, one acceleratorprogram may provide services to more than one instance of a SIMDprogram. And in at least some applications, only a minority of theinstances of a SIMD program may need acceleration, such as, for example,in sparse matrix multiplication where one instance of a SIMD programfinds itself burdened with many more calculations than would be typicalfor nodes generally in such an application.

A launcher program (135) is a module of computer program instructionsthat runs on a compute node in a SIMD partition booted in MIMD mode,receives from a MIMD dispatcher a name of a MIMD program, and executesthe MIMD program on the compute node. A launcher program may beimplemented, for example, as illustrated by these computer programinstructions:

launcher(dispatcherNetworkAddress) { socketID = socket( );connect(socketID, dispatcherNetworkAddress); read(socketID,MIMDProgramName); close(socketID); exec(MIMDProgramName); }

This example launcher program is ‘pseudocode,’ an explanation set forthin code form, not an actual working model. As shown in this pseudocodeexample, the launcher programs typically use a Unix-like exec( )function to execute MIMD programs, so that executing a MIMD programreplaces the launcher program with the MIMD program in process addressspace in computer memory of the compute node. Each compute node operatessingle-threaded, with only one thread of execution on the node. When alauncher program executes a MIMD program, the MIMD program, as a newthread of execution on a compute node that only supports one thread ofexecution, is written over the launcher program in the compute node'sprocess address space, wiping out the launcher program. The operatingsystem on the compute node, therefore, notes its set MIMD flag andre-executes a launcher program on the compute node in the SIMD partitionupon termination of the MIMD program earlier executed by a launcherprogram.

The arrangement of nodes, networks, and I/O devices making up theexemplary system illustrated in FIG. 1 are for explanation only, not forlimitation of the present invention. Data processing systems capable ofexecuting MIMD programs on a SIMD machine according to embodiments ofthe present invention may include additional nodes, networks, devices,and architectures, not shown in FIG. 1, as will occur to those of skillin the art. The SIMD machine (100) in the example of FIG. 1 includessixteen compute nodes (102)—whereas SIMD machines capable of executingMIMD programs according to embodiments of the present inventionsometimes include thousands of compute nodes. In addition to Ethernetand JTAG, networks in such data processing systems may support many datacommunications protocols including for example TCP (Transmission ControlProtocol), IP (Internet Protocol), and others as will occur to those ofskill in the art. Various embodiments of the present invention may beimplemented on a variety of hardware platforms in addition to thoseillustrated in FIG. 1.

Executing MIMD programs on a SIMD machine according to embodiments ofthe present invention is generally implemented on a parallel computerthat includes a plurality of compute nodes. In fact, such computers mayinclude thousands of such compute nodes. Each compute node is in turnitself a kind of computer composed of one or more computer processors,its own computer memory, and its own input/output adapters. For furtherexplanation, therefore, FIG. 2 sets forth a block diagram of anexemplary compute node useful for executing MIMD programs on a SIMDmachine according to embodiments of the present invention. The computenode (152) of FIG. 2 includes at least one computer processor (164) aswell as random access memory (‘RAM’) (156). Processor (164) is connectedto RAM (156) through a high-speed memory bus (154) and to othercomponents of the compute node through a bus adapter (194) and anextension bus (168).

Stored in RAM (156) is a parallel communications library (160), alibrary of computer program instructions that carry out parallelcommunications among compute nodes, including point to point operationsas well as collective operations. Application program (158) executescollective operations by calling software routines in parallelcommunications library (160). A library of parallel communicationsroutines may be developed from scratch for use in executing MIMDprograms on a SIMD machine according to embodiments of the presentinvention, using a traditional programming language such as the Cprogramming language, and using traditional programming methods to writeparallel communications routines that send and receive data among nodeson two independent data communications networks. Alternatively, existingprior art libraries may be used. Examples of parallel communicationslibraries that may be used or improved for use in executing MIMDprograms on a SIMD machine according to embodiments of the presentinvention include the ‘Message Passing Interface’ (‘MPI’) library andthe ‘Parallel Virtual Machine’ (‘PVM’) library.

Also stored in RAM (156) is an operating system (162), a module ofcomputer program instructions and routines for an application program'saccess to other resources of the compute node. It is typical for anapplication program and parallel communications library in a computenode of a SIMD machine to run a single thread of execution with no userlogin and no security issues because the thread is entitled to completeaccess to all resources of the node. The quantity and complexity oftasks to be performed by an operating system on a compute node in a SIMDmachine therefore are smaller and less complex than those of anoperating system on a serial computer with many threads runningsimultaneously. In addition, there is no video I/O on the compute node(152) of FIG. 2, another factor that decreases the demands on theoperating system. The operating system may therefore be quitelightweight by comparison with operating systems of general purposecomputers, a pared down version as it were, or an operating systemdeveloped specifically for operations on a particular SIMD machine.Operating systems that may usefully be improved, simplified, for use ina compute node for executing MIMD programs on a SIMD machine includeUNIX™, Linux™, Microsoft XP™, AIX™, IBM's i5/OS™, and others as willoccur to those of skill in the art.

Also stored in RAM (156) are a MIMD program (158), a MIMD acceleratorprogram (161), and an instance of a SIMD program (153), shown togetherfor ease of explanation, although all three would not typically bepresent in the same compute node at the same time. The instance of aSIMD program (153) would execute on a compute node in a SIMD partition(132 on FIG. 1) booted in SIMD mode, and the MIMD program (158) and theMIMD accelerator program (161) would execute on compute nodes in a SIMDpartition (130 on FIG. 1) booted in MIMD mode.

Also stored in RAM is a launcher program (135), a module of computerprogram instructions that runs on the compute node (152) in a SIMDpartition booted in MIMD mode, receives from a MIMD dispatcher a name ofa MIMD program (158), and executes the MIMD program (158) on the computenode (152). The launcher program (135) in this example is shown disposedin the RAM space of the operating system (162), presumably havingexecuted the MIMD program (158) or the MIMD accelerator program (161),which are shown here disposed in process address space (134), havingwiped the launcher program out of the process address space (134) whenthe launcher program executed a MIMD program or a MIMD acceleratorprogram.

Also stored in RAM (156) is a MIMD flag (136), a Boolean data elementwhich when set to TRUE advises the operating system that the computenode is running in MIMD mode, so that upon termination of the MIMDprogram, the operating system, rather than terminating its ownoperations as it would do if it were operating in purely SIMD mode, nowre-executes the launcher program (135). And the compute node operatesgenerally as follows:

-   -   the launcher program connects to a dispatcher (139 on FIGS. 1        and 7),    -   the launcher programs receives from the dispatcher a MIMD        program name—or the name of a MIMD accelerator program,    -   the launcher program executes the MIMD program or the MIMD        accelerator program when provided with the program name,        installing the MIMD program or the MIMD accelerator program in        process address space in RAM and wiping out the launcher        program,    -   the operating system re-executes the launcher program upon        termination of the MIMD program,    -   and so on, repeating indefinitely.

The MIMD flag advises the operating system to reload the launcherprogram when the MIMD program exits—without notifying the controlapplication (124 on FIG. 1) of the exit. In effect, compared to SIMDoperations, the MIMD mode compute node never exits. It just reloads thelauncher program and waits for another MIMD program name or MIMDaccelerator program name to execute.

Also stored in RAM (156) is a reboot flag (137), a Boolean data elementwhich when set to TRUE advises the operating system (162) that a currentboot of the operating system is a reboot, that is, that the compute nodehas already been booted at least once before as part of a SIMD partitionbooted in MIMD mode. Remember that the overall undertaking here isexecuting a MIMD program on a SIMD machine where, in fact, the SIMDmachine remains a SIMD machine. In its inception, therefore, a boot of aSIMD partition in MIMD mode is still a boot of a SIMD partition. Theboot process is modified by inclusion of a launcher program, a MIMDflag, a reboot flag, and so on, but the underlying process is a SIMDboot. The original boot, therefore, includes SIMD-type functions thatare not needed on a reboot. Examples of such SIMD-type functions includeinitializing with link training synchronous data communications amonglinks of the network among compute nodes in the SIMD partition andinitializing, with a parallel processing barrier, parallel operationsamong the compute nodes of the SIMD partition. Such SIMD-type functionsare not needed on a reboot because, for example, the data communicationslinks are already trained for synchronous operation, and there is noneed to initialize parallel processing with a parallel processingbarrier because, at the time of a reboot, there is no longer anyparallel processing in the SIMD partition booted in MIMD mode. Theoperating system (162), advised to do so by a reboot flag (137) set toTRUE, upon a reboot, omits from the boot process the initializing ofsynchronous data communications on the network with link training andthe initializing of parallel operations among the compute nodes with aparallel processing barrier.

The exemplary compute node (152) of FIG. 2 includes severalcommunications adapters (172, 176, 180, 188) for implementing datacommunications with other nodes of a SIMD machine. Such datacommunications may be carried out serially through RS-232 connections,through external buses such as USB, through data communications networkssuch as IP networks, and in other ways as will occur to those of skillin the art. Communications adapters implement the hardware level of datacommunications through which one computer sends data communications toanother computer, directly or through a network. Examples ofcommunications adapters useful in systems that execute MIMD programs ona SIMD machine according to embodiments of the present invention includemodems for wired communications, Ethernet (IEEE 802.3) adapters forwired network communications, and 802.11b adapters for wireless networkcommunications.

The data communications adapters in the example of FIG. 2 include aGigabit Ethernet adapter (172) that couples example compute node (152)for data communications to a Gigabit Ethernet (174). Gigabit Ethernet isa network transmission standard, defined in the IEEE 802.3 standard,that provides a data rate of 1 billion bits per second (one gigabit).Gigabit Ethernet is a variant of Ethernet that operates over multimodefiber optic cable, single mode fiber optic cable, or unshielded twistedpair.

The data communications adapters in the example of FIG. 2 includes aJTAG Slave circuit (176) that couples example compute node (152) fordata communications to a JTAG Master circuit (178). JTAG is the usualname used for the IEEE 1149.1 standard entitled Standard Test AccessPort and Boundary-Scan Architecture for test access ports used fortesting printed circuit boards using boundary scan. JTAG is so widelyadapted that, at this time, boundary scan is more or less synonymouswith JTAG. JTAG is used not only for printed circuit boards, but alsofor conducting boundary scans of integrated circuits, and is also usefulas a mechanism for debugging embedded systems, providing a convenient“back door” into the system. The example compute node of FIG. 2 may beall three of these: It typically includes one or more integratedcircuits installed on a printed circuit board and may be implemented asan embedded system having its own processor, its own memory, and its ownI/O capability. JTAG boundary scans through JTAG Slave (176) mayefficiently configure processor registers and memory in compute node(152) for use in executing MIMD programs on a SIMD machine according toembodiments of the present invention.

The data communications adapters in the example of FIG. 2 includes aPoint To Point Adapter (180) that couples example compute node (152) fordata communications to a network (108) that is optimal for point topoint message passing operations such as, for example, a networkconfigured as a three-dimensional torus or mesh. Point To Point Adapter(180) provides data communications in six directions on threecommunications axes, x, y, and z, through six bidirectional links: +x(181), −x (182), +y (183), −y (184), +z (185), and −z (186).

The data communications adapters in the example of FIG. 2 includes aCollective Operations Adapter (188) that couples example compute node(152) for data communications to a network (106) that is optimal forcollective message passing operations such as, for example, a networkconfigured as a binary tree. Collective Operations Adapter (188)provides data communications through three bidirectional links: two tochildren nodes (190) and one to a parent node (192).

Example compute node (152) includes two arithmetic logic units (‘ALUs’).ALU (166) is a component of processor (164), and a separate ALU (170) isdedicated to the exclusive use of collective operations adapter (188)for use in performing the arithmetic and logical functions of reductionoperations. Computer program instructions of a reduction routine inparallel communications library (160) may latch an instruction for anarithmetic or logical function into instruction register (169). When thearithmetic or logical function of a reduction operation is a ‘sum’ or a‘logical or,’ for example, collective operations adapter (188) mayexecute the arithmetic or logical operation by use of ALU (166) inprocessor (164) or, typically much faster, by use of dedicated ALU(170).

For further explanation, FIG. 3A illustrates an exemplary Point To PointAdapter (180) useful in systems that execute MIMD programs on a SIMDmachine according to embodiments of the present invention. Point ToPoint Adapter (180) is designed for use in a data communications networkoptimized for point to point operations, a network that organizescompute nodes in a three-dimensional torus or mesh. Point To PointAdapter (180) in the example of FIG. 3A provides data communicationalong an x-axis through four unidirectional data communications links,to and from the next node in the −x direction (182) and to and from thenext node in the +x direction (181). Point To Point Adapter (180) alsoprovides data communication along a y-axis through four unidirectionaldata communications links, to and from the next node in the −y direction(184) and to and from the next node in the +y direction (183). Point ToPoint Adapter (180) in also provides data communication along a z-axisthrough four unidirectional data communications links, to and from thenext node in the −z direction (186) and to and from the next node in the+z direction (185).

For further explanation, FIG. 3B illustrates an exemplary CollectiveOperations Adapter (188) useful in systems that execute MIMD programs ona SIMD machine according to embodiments of the present invention.Collective Operations Adapter (188) is designed for use in a networkoptimized for collective operations, a network that organizes computenodes of a SIMD machine in a binary tree. Collective Operations Adapter(188) in the example of FIG. 3B provides data communication to and fromtwo children nodes through four unidirectional data communications links(190). Collective Operations Adapter (188) also provides datacommunication to and from a parent node through two unidirectional datacommunications links (192).

For further explanation, FIG. 4 illustrates an exemplary datacommunications network optimized for point to point operations (106). Inthe example of FIG. 4, dots represent compute nodes (102) of a SIMDmachine, and the dotted lines between the dots represent datacommunications links (103) between compute nodes. The datacommunications links are implemented with point to point datacommunications adapters similar to the one illustrated for example inFIG. 3A, with data communications links on three axes, x, y, and z, andto and fro in six directions +x (181), −x (182), +y (183), −y (184), +z(185), and −z (186). The links and compute nodes are organized by thisdata communications network optimized for point to point operations intoa three dimensional mesh (105) that wraps around to form a torus (107).Each compute node in the torus has a location in the torus that isuniquely specified by a set of x, y, z coordinates. For clarity ofexplanation, the data communications network of FIG. 4 is illustratedwith only 27 compute nodes, but readers will recognize that a datacommunications network optimized for point to point operations for usein executing MIMD programs on a SIMD machine in accordance withembodiments of the present invention may contain only a few computenodes or may contain thousands of compute nodes. For furtherexplanation, FIG. 5 illustrates an exemplary data communications network(108) optimized for collective operations by organizing compute nodes ina tree. The example data communications network of FIG. 5 includes datacommunications links connected to the compute nodes so as to organizethe compute nodes as a tree. In the example of FIG. 5, dots representcompute nodes (102) of a SIMD machine, and the dotted lines (103)between the dots represent data communications links between computenodes. The data communications links are implemented with collectiveoperations data communications adapters similar to the one illustratedfor example in FIG. 3B, with each node typically providing datacommunications to and from two children nodes and data communications toand from a parent node, with some exceptions. Nodes in a binary tree maybe characterized as a root node (202), branch nodes (204), and leafnodes (206). The root node (202) has two children but no parent. Theleaf nodes (206) each has a parent, but leaf nodes have no children. Thebranch nodes (204) each has both a parent and two children. The linksand compute nodes are thereby organized by this data communicationsnetwork optimized for collective operations into a binary tree (108).For clarity of explanation, the data communications network of FIG. 5 isillustrated with only 31 compute nodes, but readers will recognize thata data communications network optimized for collective operations foruse in executing MIMD programs on a SIMD machine in accordance withembodiments of the present invention may contain only a few computenodes or may contain thousands of compute nodes.

In the example of FIG. 5, each node in the tree is assigned a unitidentifier referred to as a ‘rank’ (250). A node's rank uniquelyidentifies the node's location in the tree network for use in both pointto point and collective operations in the tree network. The ranks inthis example are assigned as integers beginning with 0 assigned to theroot node (202), 1 assigned to the first node in the second layer of thetree, 2 assigned to the second node in the second layer of the tree, 3assigned to the first node in the third layer of the tree, 4 assigned tothe second node in the third layer of the tree, and so on. For ease ofillustration, only the ranks of the first three layers of the tree areshown here, but all compute nodes in the tree network are assigned aunique rank.

For further explanation, FIG. 6 sets forth a functional block diagram ofan exemplary SIMD machine useful for executing MIMD programs on a SIMDmachine according to embodiments of the present invention. The SIMDmachine (100) includes compute nodes (102) that are coupled for datacommunications by several independent data communications networksincluding a high speed Ethernet network (174), a Joint Test Action Group(‘JTAG’) network (104), a collective network (106) which is optimizedfor collective operations, a point-to-point network (108) which isoptimized for point to point operations among compute nodes, and abarrier network (109) which is optimized for execution of parallelprocessing barriers. Each data communications network is implementedwith data communications links among the compute nodes (102). The datacommunications links provide data communications for parallel operationsamong the compute nodes of the SIMD partition. Point-to-point network(108) is a synchronous data communications network that includessynchronous data communications links connected among the compute nodesso as to organize the compute nodes of the SIMD partition in a mesh ortorus. Collective network (106) is a synchronous data communicationsnetwork that includes synchronous data communications links connectedamong the compute nodes so as to organize the compute nodes of the SIMDpartition in a tree structure. The point-to-point network (108) and thecollective network (106), as well as the other networks in the exampleof FIG. 1, are characterized by a network topology (161).

The SIMD machine (100) includes a service node (116) coupled to thecompute nodes through the JTAG network (104). Service node (116)provides services common to pluralities of compute nodes, loadingprograms into the compute nodes, starting program execution on thecompute nodes, retrieving results of program operations on the computernodes, and so on. Service node (116) runs service applications (143) andcommunicates with users (128) through a service application interface(126) that runs on computer terminal (122). Service applications (143)that execute on the service node (116) include:

-   -   a control application (124), which is a module of computer        program instructions that boots partitions, loads launcher        programs onto compute nodes in SIMD partitions booted in MIMD        mode, and administers error conditions detected on compute        nodes,    -   a scheduler (140), which is a module of computer program        instructions that schedules data processing jobs on the SIMD        machine, including installing SIMD programs on compute nodes and        passing MIMD jobs along to a MIMD dispatcher for execution in        SIMD partitions booted in MIMD mode; and    -   a MIMD dispatcher (139), which is a module of computer program        instructions that installs MIMD programs, including MIMD        accelerator programs, on compute nodes in SIMD partitions booted        MIMD mode.

The service applications in this example are supported by a main jobqueue (141), a MIMD job programs table (142), and a MIMD job queue(138). The main job queue (141) is represented in this example as atable with columns for a job identification code, a job type code, and acolumn specifying the number of compute nodes needed to execute a job.Each record in the main job queue (141) represents either a MIMD job ora SIMD job. Each SIMD job represents a single SIMD program that will runidentically on each compute node (102) in a SIMD partition booted inSIMD mode. Each MIMD job represents one or more MIMD programs that willbe executed on one or more compute nodes of a SIMD partition booted inMIMD mode.

The main job queue (141) in this example is represented in a one-to-manydata modeling relationship with the MIMD job programs table (142) usingthe job identification code as a foreign key. Each SIMD job isimplemented with a single SIMD program, but a MIMD job, requiring nostrict parallelism, no collective operations, no parallel processingbarriers, can be composed of any number of individual MIMD programswhich may be executed asynchronously with respect to one another. So inthis example, the MIMD job identified by job code “J1” is composed ofthree MIMD programs, “Prog1,” “Prog2,” and “Prog3.” Similarly, the MIMDjob identified by job code “J2” is composed of four MIMD programs,“Prog4,” “Prog5,” “Prog6,” and “Prog7.”

The scheduler (140) only loads and executes SIMD jobs (146). Thescheduler is optimized to load the same SIMD program onto each and everycompute node of the SIMD machine, but loading a MIMD job requiresloading multiple separate, individual programs onto separate computenodes, a process for which the MIMD dispatcher is optimized. When thescheduler (140) encounters a MIMD job in the main job queue (141),therefore, the scheduler hands that job off to the MIMD dispatcher(139), which then loads and executes the MIMD job (145). The scheduler(140) hands off MIMD jobs to the MIMD dispatcher (130) by registeringthe jobs in the MIMD job queue (138), represented here as a table withtwo columns, a job identification and a representation of the number ofcompute nodes needed for each MIMD job, where each record in the MIMDjob queue represents a MIMD job to be dispatched for execution by theMIMD dispatcher (139). The MIMD dispatcher (139) dispatches MIMD jobsfor execution by communicating the name of MIMD programs comprising aMIMD job to individual launcher programs running on individual computenodes in a SIMD partition (130) booted in MIMD mode.

In the example of FIG. 6, the SIMD machine supports partitioning, andeach partition can be booted either in SIMD mode or in MIMD mode. When aSIMD partition (132) is booted in SIMD mode, the entire partition isbooted in SIMD mode, and instances of one SIMD program at a time will berun on all the compute nodes of the partition. When a SIMD partition(130) is booted in MIMD mode, the entire partition is booted in MIMDmode, and multiple MIMD programs can then be run on any or all of thecompute nodes of the partition. A control application (124) according toembodiments of the present invention can establish on a SIMD machine aSIMD partition booted in MIMD mode, with a SIMD partition booted in SIMDmode running simultaneously with the SIMD partition booted in MIMD mode.On such a SIMD machine, multiple MIMD applications may be runsimultaneously in one partition while SIMD applications are run inanother partition, all on the same machine at the same time.

In the example of FIG. 1, all the compute nodes (102) are initiallyconfigured exclusively for SIMD operations, and the system of FIG. 1operates generally to execute MIMD programs (158, 161) on a SIMD machine(100) according to embodiments of the present invention by establishingon the SIMD machine a plurality of SIMD partitions (130, 132); booting afirst SIMD partition (130) in MIMD mode; executing, on a compute node(102) of the first SIMD partition (130) booted in MIMD mode, a MIMDaccelerator program (161); executing a SIMD program (151) in a secondSIMD partition (132), one instance (153, 155, 157, 159) of the SIMDprogram (151) executing on each compute node (102) of the second SIMDpartition (132), each instance of the SIMD program carrying out aportion of the data processing effected by the SIMD program; andaccelerating, by an instance of the SIMD program through the MIMDaccelerator program, a portion of the data processing of the instance ofthe SIMD program.

For further explanation, FIG. 7 sets forth a flow chart illustrating anexemplary method for executing MIMD programs on a SIMD machine accordingto embodiments of the present invention. The method of FIG. 7 is carriedout on a SIMD machine similar to the SIMD machines described above (100on FIG. 1). That is, the method of FIG. 7 is carried out on a SIMDmachine that includes a number of compute nodes, where each compute nodeis capable of executing only a single thread of execution, and thecompute nodes are initially configured exclusively for SIMD operations.The SIMD machine includes at least one data communications network (106,108 on FIG. 1) that includes synchronous data communications links amongthe compute nodes.

The method of FIG. 7 includes establishing (302) a plurality of SIMDpartitions (130, 132 on FIG. 1), where each SIMD partition includes aplurality of compute nodes (102 on FIG. 1). The compute nodes in eachSIMD partition are electronically isolated from compute nodes in otherpartitions of the SIMD machine. The compute nodes in each SIMD partitionare coupled to one another through links of a network (106 or 108 onFIG. 1) for synchronous data communications for parallel SIMD operationsamong the compute nodes in each SIMD partition.

The method of FIG. 7 also includes booting (304) a first SIMD partitionin MIMD mode (130 on FIG. 1). Booting SIMD partitions in MIMD mode isexplained in more detail below with reference to FIG. 8.

The method of FIG. 7 also includes executing (314), on a compute node ofthe first SIMD partition booted in MIMD mode, a MIMD acceleratorprogram. In the method of FIG. 7, executing (314) a MIMD acceleratorprogram is carried out by providing (320) by a dispatcher a name of aMIMD accelerator program to a launcher on a compute node in the firstSIMD partition booted in MIMD mode and launching (322) by the launcherprogram the MIMD accelerator program on the compute node. The launcherprogram typically launches the MIMD accelerator program by use of aUnix-like exec( ) function that wipes the launcher program from processmemory, overlaying it with the MIMD accelerator program.

The method of FIG. 7 also includes executing (316) a SIMD program in asecond SIMD partition, one instance of the SIMD program executing oneach compute node of the second SIMD partition. Each instance of theSIMD program carries out a portion of the data processing effectedoverall by the SIMD program.

The method of FIG. 7 also includes accelerating (318), by an instance ofthe SIMD program through the MIMD accelerator program, a portion of thedata processing of the instance of the SIMD program. In the method ofFIG. 7, accelerating (318) a portion of the data processing of theinstance of the SIMD program is carried out by transferring (324) a partof the data processing from the instance of the SIMD program to theaccelerator program. The portion of data processing is transferred byuse of a data communications network such as one of the networksdescribed above with regard to references 104, 106, 108, 109, and 174 onFIG. 1. The portion of data processing so transferred may be data only,where all the executable code for acceleration is already a component ofthe accelerator program, or, alternatively, the portion of dataprocessing so transferred may include both data whose processing is tobe accelerated as well as executable code.

FIG. 8 sets forth a flow chart illustrating an exemplary method ofbooting (304) a SIMD partition (130 on FIG. 1) in MIMD mode according toembodiments of the present invention. In the example of FIG. 8, booting(304) a SIMD partition in MIMD mode includes setting (306), in operatingsystems on the compute nodes of the SIMD partition, flags indicatingMIMD operation. Such flags are Boolean data elements, and setting themmeans setting them to TRUE. Booting (304) a SIMD partition in MIMD modealso includes loading (307) onto the compute nodes of the SIMD partitiona launcher program (135 on FIG. 1), one instance of the launcher programon each compute node in the SIMD partition booted in MIMD mode.

In this example, booting (304) a SIMD partition in MIMD mode alsoincludes initializing (308) with link training synchronous datacommunications among links of the network among compute nodes in theSIMD partition. Link training is an initialization process for links ina high performance network that uses specific data packet types known astraining sequences to enable each link to determine its link width,polarity, device presence, and also to detect problems in the link.

Booting (304) the SIMD partition in MIMD mode in this example alsoincludes initializing (310), with a parallel processing barrier,parallel operations among the compute nodes of the SIMD partition. Aparallel processing barrier is a parallel processing function, typicallyimplemented as a member of a message passing library such as MPI, thatsynchronizes operation of all processes executing in a SIMD partition.All processes in the partition contain a call to a barrier at a point inprocessing where all the processes need to be synchronized. Each processthat calls the barrier function waits to continue processing until allof the processes in the partition have called the barrier function. Itis not uncommon for high performance SIMD machines to implement barrierswith special hardware support, as is the case for the SIMD machinedescribed above with reference to FIG. 1. That SIMD machine has anindependent data communication network (109 on FIG. 1) dedicated to theexecution of barriers.

Booting (304) the SIMD partition in MIMD mode in the example of FIG. 8also includes executing (312) a launcher program (135 on FIG. 1) on eachcompute node in the SIMD partition. A launcher program (135), asdescribed above in more detail, is a module of computer programinstructions that runs on a compute node in a SIMD partition booted inMIMD mode, receives from a MIMD dispatcher a name of a MIMD program, andexecutes the MIMD program on the compute node.

For further explanation, FIG. 9 sets forth a flow chart illustrating afurther exemplary method for executing MIMD programs on a SIMD machineaccording to embodiments of the present invention. The method of FIG. 9is similar to the method of FIG. 7, carried out on a SIMD machinesimilar to those described above and including as it does establishing(302) a plurality of SIMD partitions;

booting (304) a first SIMD partition in MIMD mode; executing (314), on acompute node of the first SIMD partition booted in MIMD mode, a MIMDaccelerator program; executing (316) a SIMD program in a second SIMDpartition; accelerating (318), by an instance of the SIMD programthrough the MIMD accelerator program, a portion of the data processingof the instance of the SIMD program—all of which—subject to theexceptions described just below in this specification—function in asimilar manner as described above with regard to the method of FIG. 7.

In the method of FIG. 9, unlike the method of FIG. 7, executing (314) aMIMD accelerator program is carried out by providing (326) by theinstance of the SIMD program the MIMD accelerator program to a launcheron a compute node in the first SIMD partition booted in MIMD mode andlaunching (322) by the launcher the accelerator program on the computenode. That is, in the method of FIG. 7, it is the instance of the SIMDprogram rather than the dispatcher that provides the accelerator programto the launcher. The instance of the SIMD program may provide theaccelerator program to the launcher literally, as an executable moduleof computer program instructions, or by name, by providing a name of aMIMD accelerator program for the launcher to load from disk. In thisway, the MIMD accelerator program is executed only when it is actuallyneeded rather than being dispatched by a dispatcher to occupy computerresources waiting for a request for acceleration that may never come.

Also in the method of FIG. 9, unlike the method of FIG. 7, accelerating(318) a portion of the data processing of the instance of the SIMDprogram is carried out by calculating (328) an amount of time requiredfor executing by the SIMD program the portion of the data processing andaccelerating (330) data processing for the portion of the dataprocessing only if the amount of time required for executing the portionby the SIMD program exceeds a predefined threshold amount. In sparsematrix multiplication, for example, when the only duty of an instance ofa SIMD program is to multiply by zero, it needs no acceleration. Whenanother instance must carry out a complex, floating pointmultiplication, requiring much more time than multiplying by zero, and abarrier is approaching, acceleration is needed. The benefit of thismethod is too help all instances of the SIMD partition to execute thebarrier as near simultaneously as possible. If even one instance is verylate to the barrier, all the other instances of the SIMD program arewasting processing time waiting for the late instance to arrive at thebarrier.

Exemplary embodiments of the present invention are described largely inthe context of a fully functional computer system for executing MIMDprograms on a SIMD machine. Readers of skill in the art will recognize,however, that the present invention also may be embodied in a computerprogram product disposed on computer readable, signal bearing media foruse with any suitable data processing system. Such signal bearing mediamay be transmission media or recordable media for machine-readableinformation, including magnetic media, optical media, or other suitablemedia. Examples of recordable media include magnetic disks in harddrives or diskettes, compact disks for optical drives, magnetic tape,and others as will occur to those of skill in the art. Examples oftransmission media include telephone networks for voice communicationsand digital data communications networks such as, for example,Ethernets™ and networks that communicate with the Internet Protocol andthe World Wide Web.

Persons skilled in the art will immediately recognize that any computersystem having suitable programming means will be capable of executingthe steps of the method of the invention as embodied in a programproduct. Persons skilled in the art will recognize immediately that,although some of the exemplary embodiments described in thisspecification are oriented to software installed and executing oncomputer hardware, nevertheless, alternative embodiments implemented asfirmware or as hardware are well within the scope of the presentinvention.

It will be understood from the foregoing description that modificationsand changes may be made in various embodiments of the present inventionwithout departing from its true spirit. The descriptions in thisspecification are for purposes of illustration only and are not to beconstrued in a limiting sense. The scope of the present invention islimited only by the language of the following claims.

1. A method of executing Multiple Instructions Multiple Data (‘MIMD’)programs on a Single Instruction Multiple Data (‘SIMD’) machine, theSIMD machine comprising a plurality of compute nodes, each compute nodecapable of executing only a single thread of execution, the plurality ofcompute nodes initially configured exclusively for SIMD operations, theSIMD machine further comprising a data communications network, the datacommunications network comprising synchronous data communications linksamong the plurality of compute nodes, the method comprising:establishing on the SIMD machine a plurality of SIMD partitions, eachSIMD partition comprising a plurality of the compute nodes, theplurality of compute nodes in each SIMD partition electronicallyisolated from compute nodes in other partitions of the SIMD machine andcoupled to one another through links of the data communications networkfor synchronous data communications for parallel SIMD operations amongthe plurality of compute nodes in each SIMD partition; booting a firstSIMD partition in MIMD mode; executing, on a compute node of the firstSIMD partition booted in MIMD mode, a MIMD accelerator program;executing a SIMD program for effecting a data processing in a secondSIMD partition, one instance of the SIMD program executing on eachcompute node of the second SIMD partition, each instance of the SIMDprogram carrying out a portion of the data processing effected by theSIMD program; and accelerating, by an instance of the SIMD programthrough the MIMD accelerator program, a portion of the data processingof the instance of the SIMD program, the accelerating further comprisingthe steps of: calculating an amount of time required for executing bythe SIMD program the portion of the data processing; and acceleratingdata processing for the portion of the data processing only if theamount of time required for executing the portion by the SIMD programexceeds a predefined threshold amount.
 2. Apparatus for executingMultiple Instructions Multiple Data (‘MIMD’) programs on a SingleInstruction Multiple Data (‘SIMD’) machine, the SIMD machine comprisinga plurality of compute nodes, each compute node capable of executingonly a single thread of execution, the plurality of compute nodesinitially configured exclusively for SIMD operations, the SIMD machinefurther comprising a data communications network, the datacommunications network comprising synchronous data communications linksamong the plurality of compute nodes, the apparatus comprising acomputer processor, a computer memory operatively coupled to thecomputer processor, the computer memory having disposed within itcomputer program instructions capable of: establishing on the SIMDmachine a plurality of SIMD partitions, each SIMD partition comprising aplurality of the compute nodes, the plurality of compute nodes in eachSIMD partition electronically isolated from compute nodes in otherpartitions of the SIMD machine and coupled to one another through linksof the data communications network for synchronous data communicationsfor parallel SIMD operations among the plurality of compute nodes ineach SIMD partition; booting a first SIMD partition in MIMD mode;executing, on a compute node of the first SIMD partition booted in MIMDmode, a MIMD accelerator program; executing a SIMD program for effectinga data processing in a second SIMD partition, one instance of the SIMDprogram executing on each compute node of the second SIMD partition,each instance of the SIMD program carrying out a portion of the dataprocessing effected by the SIMD program; and accelerating, by aninstance of the SIMD program through the MIMD accelerator program, aportion of the data processing of the instance of the SIMD program, theaccelerating further comprising: calculating an amount of time requiredfor executing by the SIMD program the portion of the data processing;and accelerating data processing for the portion of the data processingonly if the amount of time required for executing the portion by theSIMD program exceeds a predefined threshold amount.
 3. A computerprogram product for executing Multiple Instructions Multiple Data(‘MIMD’) programs on a Single Instruction Multiple Data (‘SIMD’)machine, the SIMD machine comprising a plurality of compute nodes, eachcompute node capable of executing only a single thread of execution, theplurality of compute nodes initially configured exclusively for SIMDoperations, the SIMD machine further comprising a data communicationsnetwork, the data communications network comprising synchronous datacommunications links among the plurality of compute nodes, the computerprogram product disposed in a computer readable recordable medium, thecomputer program product comprising computer program instructionscapable of: establishing on the SIMD machine a plurality of SIMDpartitions, each SIMD partition comprising a plurality of the computenodes, the plurality of compute nodes in each SIMD partitionelectronically isolated from compute nodes in other partitions of theSIMD machine and coupled to one another through links of the datacommunications network for synchronous data communications for parallelSIMD operations among the plurality of compute nodes in each SIMDpartition; booting a first SIMD partition in MIMD mode; executing, on acompute node of the first SIMD partition booted in MIMD mode, a MIMDaccelerator program; executing a SIMD program for effecting a dataprocessing in a second SIMD partition, one instance of the SIMD programexecuting on each compute node of the second SIMD partition, eachinstance of the SIMD program carrying out a portion of the dataprocessing effected by the SIMD program; and accelerating, by aninstance of the SIMD program through the MIMD accelerator program, aportion of the data processing of the instance of the SIMD program, theaccelerating further comprising the steps of: calculating an amount oftime required for executing by the SIMD program the portion of the dataprocessing; and accelerating data processing for the portion of the dataprocessing only if the amount of time required for executing the portionby the SIMD program exceeds a predefined threshold amount.